1. G.R. Wiggans 1, T.S. Sonstegard 1, P.M. VanRaden 1, L.K. Matukumalli 1,2, R.D. Schnabel 3, J.F. Taylor 3, J.P. Chesnais 4, F.S. Schenkel 5, and C.P. Van Tassell 1 1 Agricultural Research Service, United States Department of Agriculture, Beltsville, MD, USA 2 Bioinformatics and Computational Biology, George Mason University, Manassas, VA, USA 3 Division of Animal Sciences, University of Missouri, Columbia, MO, USA 4 Semex Alliance, Guelph, ON, Canada 5 University of Guelph, Guelph, ON, Canada george.wiggans@ars.usda.gov 2008 ICAR 2008 – Genomics (1)G.R. Wiggans Genomic evaluations in the United States and Canada: A collaboration

2. G.R. Wiggans 2008 ICAR 2008 – Genomics (2) DNA sources l Cooperative Dairy DNA Repository (CDDR) w Progeny-test bull semen contributed by 7 artificial-insemination (AI) organizations w Currently over 20,000 bulls included l Bulls and cows nominated by AI organizations l Cooperator contributions to research projects l Specific semen purchases

3. G.R. Wiggans 2008 ICAR 2008 – Genomics (3) Genotyping laboratories l Bovine Functional Genomics Laboratory (BFGL), USDA (Beltsville, MD) l University of Missouri (Columbia, MO) l University of Alberta (Edmonton, AB) l Illumina (San Diego, CA) l Genetics & IVF Institute (Fairfax, VA) l GeneSeek (Lincoln, NE)

4. G.R. Wiggans 2008 ICAR 2008 – Genomics (4) SNP selection l Minor allele frequency (MAF) > 0.05 l Portion heterozygous within 0.07 of expected l SNP with clustering problems eliminated l Redundant SNP eliminated l 38,416 SNP remained l MAF uniform 0.05 to 0.50 l Some unreadable SNP may be recovered

5. G.R. Wiggans 2008 ICAR 2008 – Genomics (5) Accurate evaluations l Accurate genomic evaluations require estimates of SNP effects l Evaluations with high reliability provide the most information l Recent animals are more useful than ones from earlier generations l Reliability of genomic evaluations increases with number of predictor animals

6. G.R. Wiggans 2008 ICAR 2008 – Genomics (6) Holsteins genotyped

7. G.R. Wiggans 2008 ICAR 2008 – Genomics (7) Genomic evaluation & reliability l Calculate parent average (PA) based only on genotyped animals with best linear unbiased prediction l Combine traditional PA (or evaluation) with genomic PA and evaluation using selection index weights l Update traditional evaluation with additional information from genomics l Reliability from inverse of genomic relationship matrix

8. G.R. Wiggans 2008 ICAR 2008 – Genomics (8) Data & evaluation flow Animal Improvement Programs Laboratory, USDA Artificial- insemination organizations Dairy producers DNA laboratories samples evaluations genotypes nominations evaluations

9. G.R. Wiggans 2008 ICAR 2008 – Genomics (9) Schedule l Calculate SNP effects with each of 3 annual traditional evaluations l Calculate genomic evaluations 1 or more times between runs w Recalculate SNP effects if significant number of predictor animals added w Use existing SNP effects if only young animals added

10. G.R. Wiggans 2008 ICAR 2008 – Genomics (10) Official release in 2009 l Added accuracy of genomic evaluations propagated to evaluations of relatives without genotyping l Public release of genomic evaluations w Cows soon after calculated w Bulls when enrolled with NAAB or Canadian AI organization w Shared by agreement with owner

11. G.R. Wiggans 2008 ICAR 2008 – Genomics (11) Research at Guelph in 2004-2007 l Affymetrix 10,000 SNP panel l About 6,000 SNP usable for genomic selection l Many clusters l Study of a wide range of genomic methods

12. G.R. Wiggans 2008 ICAR 2008 – Genomics (12) Project at Guelph-10,000 markers- 820 bulls TraitPA-reliabilityGEBV- reliability Protein yield 38 46 Fat yield 38 43 SCS 30 48 Conformation 39 47

13. G.R. Wiggans 2008 ICAR 2008 – Genomics (13) Research in Canada l Development of GEBV for Canadian traits using data from USDA project: summer 2008 l Research collaboration with USDA: w Genomic methods w Combining genomic and phenotypic data w Single SNP vs haplotypes w Other topics

14. G.R. Wiggans 2008 ICAR 2008 – Genomics (14) GEBV in Canada l CDN: official GEBV planned for 2009 l Same approach as US: w One EBV figure using any genomic data available w All GEBV public when calculated

15. G.R. Wiggans 2008 ICAR 2008 – Genomics (15) Benefits of collaboration l Share genotypes l Collaborate on methods l Harmonize policy l Exchange domestic evaluations before release date for use in SNP effect estimation

16. G.R. Wiggans 2008 ICAR 2008 – Genomics (16) Interbull l Can process genomic evaluations l Genomics contribution to accuracy should be reported w Avoid double counting when submitted by multiple countries w Could be processed similar to parent contribution l Change in 10-herd requirement needed to allow marketing bulls with only genomic information in countries without genomic evaluations

17. G.R. Wiggans 2008 ICAR 2008 – Genomics (17) Implications l Era of genomic prediction has begun l Young bull acquisition and marketing as well as cow selection will use genomic data l Routine genotyping and validation will become industry rather than research responsibilities

18. G.R. Wiggans 2008 ICAR 2008 – Genomics (18) Financial support l National Research Initiative grants, USDA l Natl. Assoc. of Animal Breeders (NAAB, Columbia, MO) w ABS Global (DeForest, WI) w Accelerated Genetics (Baraboo, WI) w Alta (Balzac, AB) w Genex (Shawano, WI) w New Generation Genetics (Fort Atkinson, WI) w Select Sires (Plain City, OH) w Semex Alliance (Guelph, ON) w Taurus-Service (Mehoopany, PA) l Agricultural Research Service, USDA